scholarly journals Impact of COVID-19 on monthly water consumption on a tropical tourism island: case study of Phuket (Thailand)

2021 ◽  
Author(s):  
Jiramate Changklom ◽  
Tas Surasanwong ◽  
Praewa Jowwongsan ◽  
Surachai Lipiwattanakarn ◽  
Adichai Pornprommin
Keyword(s):  
Water Demand ◽  
Demand Forecasting ◽  
Calendar Period ◽  
State Of Emergency ◽  
Tropical Island ◽  
Forecasting Models ◽  
Cascade Regression ◽  
Residential Consumption ◽  
The Impact

Abstract Phuket is a tropical island in Thailand that is famous for tourism. The COVID-19 pandemic resulted in the number of tourists reducing to almost zero. Since tourism contributes around one-half of the gross provincial product of Phuket, the impact was so severe that even the numbers of people employed and registered as locals decreased. Analysing the data from January 2015 to March 2021, we found that the total, residential and non-residential monthly consumptions dropped significantly after Thailand's State of Emergency was declared in March 2020. Unlike other studies that reported residential consumption increasing when people are required to stay home for a prolonged period, Phuket's residential consumption decreased by more than 10% from the pre-COVID-19 level, possibly due to the drop in peer-to-peer accommodation bookings. To study the impact on consumption in detail, we modelled using cascade regression analysis by dividing the predictors into three groups, namely socioeconomics, weather and calendar period. The results showed that the number of guest arrivals was the most statistically significant in all types of consumption and should be used as a predictor for water demand forecasting models in tourism areas.

scholarly journals Variable selection methods for water demand forecasting in Ethiopia: Case study Gondar town

2018 ◽  
Vol 4 (1) ◽  
pp. 1537067 ◽  
Author(s):  
Mohammed Gedefaw ◽  
Wang Hao ◽  
Yan Denghua ◽  
Abel Girma ◽  
Mustafa Ibrahim Khamis
Keyword(s):  
Variable Selection ◽  
Water Demand ◽  
Demand Forecasting ◽  
Selection Methods ◽  
Water Demand Forecasting ◽  
Gondar Town

scholarly journals Artificial Neural Networks for Urban Water Demand Forecasting: A Case Study

2019 ◽  
Vol 1284 ◽  
pp. 012004 ◽  
Author(s):  
Leandro L Lorente-Leyva ◽  
Jairo F Pavón-Valencia ◽  
Yakcleem Montero-Santos ◽  
Israel D Herrera-Granda ◽  
Erick P Herrera-Granda ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Water Demand ◽  
Demand Forecasting ◽  
Urban Water ◽  
Water Demand Forecasting ◽  
Urban Water Demand ◽  
Artificial Neural

scholarly journals Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona Case Study.

2014 ◽  
Vol 47 (3) ◽  
pp. 10457-10462 ◽  
Author(s):  
Ajay Kumar Sampathirao ◽  
Juan Manuel Grosso ◽  
Pantelis Sopasakis ◽  
Carlos Ocampo-Martinez ◽  
Alberto Bemporad ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Demand ◽  
Large Scale ◽  
Demand Forecasting ◽  
Optimal Operation ◽  
Water Networks ◽  
Water Demand Forecasting

scholarly journals Improving the Performance of Water Demand Forecasting Models by Using Weather Input

2014 ◽  
Vol 70 ◽  
pp. 93-102 ◽  
Author(s):  
M. Bakker ◽  
H. van Duist ◽  
K. van Schagen ◽  
J. Vreeburg ◽  
L. Rietveld
Keyword(s):  
Water Demand ◽  
Demand Forecasting ◽  
Forecasting Models ◽  
Water Demand Forecasting

Artificial Neural Networks for Bottled Water Demand Forecasting: A Small Business Case Study

2019 ◽  
pp. 362-373 ◽  
Author(s):  
Israel D. Herrera-Granda ◽  
Joselyn A. Chicaiza-Ipiales ◽  
Erick P. Herrera-Granda ◽  
Leandro L. Lorente-Leyva ◽  
Jorge A. Caraguay-Procel ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Small Business ◽  
Water Demand ◽  
Demand Forecasting ◽  
Business Case ◽  
Bottled Water ◽  
Water Demand Forecasting ◽  
Business Case Study

scholarly journals Forecasting of Electrical Generation Using Prophet and Multiple Seasonality of Holt–Winters Models: A Case Study of Kuwait

2020 ◽  
Vol 10 (23) ◽  
pp. 8412
Author(s):  
Abdulla I. Almazrouee ◽  
Abdullah M. Almeshal ◽  
Abdulrahman S. Almutairi ◽  
Mohammad R. Alenezi ◽  
Saleh N. Alhajeri ◽  
...  
Keyword(s):  
Electricity Generation ◽  
Performance Metrics ◽  
Resource Planning ◽  
Superior Performance ◽  
Forecasting Models ◽  
The Third ◽  
Electrical Generation ◽  
The Impact

Electrical generation forecasting is essential for management and policymakers due to the crucial data provided for resource planning. This research employs the Prophet model with single and multiple regressors to forecast the electricity generation in Kuwait from 2020 to 2030. In addition, multiple seasonality Holt–Winters models were utilized as a benchmark for comparative analysis. The accuracy, generalization, and robustness of the models were assessed based on different statistical performance metrics. The triple seasonality Holt–Winters model achieved superior performance compared with the other models with R2 = 0.9899 and MAPE = 1.76%, followed by the double seasonality Holt–Winters model with R2 = 0.9893 and MAPE = 1.83%. Moreover, the Prophet model with multiple regressors was the third-best performing model with R2 = 0.9743 and MAPE = 2.77%. The forecasted annual generation in the year 2030 resulted in 92,535,555 kWh according to the best performing model. The study provides an outlook on the medium- and long-term electrical generation. Furthermore, the impact of fuel cost is investigated based on the five forecasting models to provide an insight for Kuwait’s policymakers.

A Comparison of Short-Term Water Demand Forecasting Models

2019 ◽  
Vol 33 (4) ◽  
pp. 1481-1497 ◽  
Author(s):  
E. Pacchin ◽  
F. Gagliardi ◽  
S. Alvisi ◽  
M. Franchini
Keyword(s):  
Water Demand ◽  
Demand Forecasting ◽  
Short Term ◽  
Forecasting Models ◽  
Water Demand Forecasting
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